%0 Journal Article
%T Deep Web complex matching method based on association mining and semantic clustering<br>基于关联挖掘和语义聚类的Deep Web复杂匹配方法*
%A CAO Qing-huang
%A JU Shi-guang
%A YANG Xiao-qin
%A <br>曹庆皇
%A 鞠时光
%A 杨晓琴
%J 计算机应用研究
%D 2009
%I 
%X In order to improve the efficiency and accuracy of Deep Web interface matching, this paper presented a method based on the existing dual correlation mining (DCM) method using association mining and semantic clustering. While digging group attributed by using correlation algorithm, introduced and realized a new correlation measure based on mutual information by matrix to resolve the inefficiency problem. Clustered the attributes to synonymous attributes by their similarity which was computed by using semantic net. By the comparison on more than 200 interfaces in 4 domains, the experiment results indicate that the improved method has greatly heighted than DCM in the respect of efficiency and accuracy.
%K Deep Web
%K correlation mining based on matrix
%K semantic clustering
%K complex matching
%K semantic net<br>Deep
%K Web
%K 矩阵关联挖掘
%K 语义聚类
%K 复杂匹配
%K 语义网
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C938DB0D9DDF0884E4E792A1E5A42F18&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=59906B3B2830C2C5&sid=D32B9E1B9C7E3D6C&eid=50E6DB5CDAAFDCB0&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=8